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The recurring racial bias in AI and Machine Learning

WP2: Responsible Data Science

Recently, there was a case that brought up - once again - the issue of bias in machine learning algorithms.

This is not a new issue per se, as in 2015 a black software developer tweeted about Google’s Photo service labelling him and a friend as “gorillas”. In 2018, a WIRED story highlighted that Google was still struggling to fix the issue with its software, and had resolved to removing the term “gorilla” and other primates from its image labelling lexicon.

GDELT: a unique, massive and open dataset for unfolding and understanding our society

Exploratory: Demography, Economy and Finance 2.0
 

Have you ever imagined a global database of society easily accessible and open for real time research? The Global Dataset of Events Location and Tone, or simply called GDELT (https://www.gdeltproject.org/) promises to be such a database, and it is supported by Google Jigsaw.

How digital data is changing how we measure well-being and happiness

What is well-being, and how can we measure it? This complex question has fascinated philosophers and thinkers since ancient times. For example, Aristotle has expressed his interest on the topic claiming that human well-being, labeled as eudaimonia (greek: ευδαιμονία: Eu=Good, Daimon=spirit), is an activity of the soul expressing complete virtue [11].

Transparency Issues in Tracing COVID-19

A need for new technological tools has emerged during the current Sars-Cov-2 pandemic. In particular, several mobile applications based on digital tracking and contact tracing have been developed, with ethical implications that have been addressed differently by a number of countries.

The SoBigData community published a white paper, entitled “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment” (https://bit.ly/whitepaper_covid_sobigdata). The white paper states:

Human migration: the Big Data perspective

Human migration is a constant phenomenon in human history, and its study involves numerous research fields. To date, data not typically used for studying migration are increasingly available. These include the so-called social Big Data: digital traces left by humans through cell phones, online social networks, and online services. More and more technologies can be employed to extract information from these large datasets. However, how can Big Data help to understand the migration phenomenon?

SoBigData Webinar - Epidemics and the city: how human mobility and well-being changed during the COVID-19 era

How did the COVID-19 epidemics change our mobility habits, and how did it impact on people’s well-being and on the virus transmissibility?

In the first webinar of the seminar series organized by SoBigData, we will address these questions, as well as many others, from the perspective of Data Science and Environmental Epidemiology.

Natural Language Processing: Attention is Explanation

Sentiment Analysis is a sub-field of Natural Language Processing (NLP) that, combining tools and techniques from Linguistics and Computer Science, aims at systematically identifying, extracting, and studying emotional states and personal opinion in natural language.

Intensity vs Accuracy: Technical-tactical differences between male and female football teams

Women's football took its first steps since the early twentieth-century. Unfortunately, the ostracism from the English Football Association drastically slowed down its development, which experienced a long period of stagnation. Women's football resurfaced in the 1960s in the Nordic countries of Europe, and it is now spreading all over the world. From 2012 the number of women academies has doubled, with around 40 million girls and women playing football worldwide nowadays.

Self-Adaptive Trajectory Segmentation
Thanks to the wide diffusion of localization technologies and mobile services based on the positioning of users and devices, the availability of mobility traces is increasing fast in several application domains. Location-based services provided through smartphones are nowadays extremely popular and the vast amounts of data that this trend leads to produce and collect open the door to several opportunities of converting them into better services, economical returns, more sustainable cities, improved living conditions, etc.